Integration of Habitat Risk Score in Radiation Therapy for Prostate Cancer

Adding a simultaneous focal radiation boost to prostate cancer lesions improves the effectiveness of radiation therapy (RT) without increasing toxicity. Reliable and reproducible ways for segmenting the gross prostate tumor volume (GTVp) for delivery of the boost are needed for the wider adoption of the technique. We propose Habitat Risk Score (HRS) maps for automatic contouring of the GTV and describe a platform for integration of HRS into RT of patients with prostate cancer.

HRS is a multiparametric magnetic resonance imaging (mpMRI) analysis technique that assigns on a pixel-by-pixel basis a score from 1 to 10 in increasing fashion with tumor aggressiveness as defined by the Gleason Score in radical prostatectomy specimens. HRS is displayed as a heat map and is used for assigning targets for prostate biopsy. HRS was evaluated in patients enrolled in a clinical trial for delivering RT boost. HRS-guided fusion biopsy procedure was prospectively evaluated in patients enrolled in the trial. The HRS6 volume, defined by pixels with a score of 6, was used to guide the GTVp segmentation, and the HRS6 association with tumor aggressiveness (Grade Group (GG), Prostate Specific Antigen (PSA), and genomic signatures Decipher) was investigated. Logistic regression models were used to assess the power of HRS6 in discriminating: (i) clinically significant (GG1 vs GG2+), (ii) intermediate (GG1, GG2 vs GG3+), and (iii) high-risk cancer (GG1, GG2, GG3 vs GG4+). Finally, the ability of HRS6 radiomics features to model Decipher was investigated.

HRS-guided fusion biopsy procedure yielded a significantly higher percentage of positive cores than in the reference procedure. HRS6 showed significant correlation with PSA, GG, and Decipher (P < .0001). AUC of HRS6 for identifying clinically significant, intermediate, and high-risk cancer was 0.76, 0.81, and 0.85. The radiomics prediction models correlated with Decipher score and when combined with clinical variables improved performance, with average AUCs of 0.79 vs 0.87 (lesion-level) and 0.84 vs 0.94 (patient-level).

The HRS approach standardizes and enhances tumor localization, thereby enabling consistent and accurate GTVp delineation. The HRS approach takes objectivity of assessment to a higher level and has been streamlined for broader adoption.